Psy325 Week 1 Assignment Data Set 1: Ratio Scale Variable

Psy325 Week 1 Assignment Data Set1ratio Scale Variablethe Bookkeeper F

The bookkeeper for a bakery noted that the first 20 days of sales of a new item were as follows. Day Number sold: 1, 2, 3, 4, 6, 7, 8, 8, 8, 9, 10, 11, 12, 13, 16, 18, 22, 24, 26, 30. Using either Excel or an online calculator, compute the descriptive statistics for this dataset, including measures such as mean, median, mode, range, variance, and standard deviation. Provide a detailed interpretation of these statistics to understand the sales pattern and variability over the first 20 days. Include in your discussion how these statistical measures inform business decisions related to inventory, staffing, or sales strategies based on the sales trend observed.

Paper For Above instruction

The analysis of sales data over a period provides vital insights into customer behavior, inventory management, and forecasting future demand, especially for a new product introduction. In this context, the first 20 days of sales data for a bakery’s new item reflect important patterns. This paper presents a comprehensive descriptive statistical analysis of the given data set, elucidating key measures such as central tendency, variability, and distribution characteristics, and discusses their implications for business decision-making.

Starting with the data itself, the sales figures across 20 days are as follows: 1, 2, 3, 4, 6, 7, 8, 8, 8, 9, 10, 11, 12, 13, 16, 18, 22, 24, 26, and 30. These numbers were organized in ascending order to facilitate statistical analysis. The primary goal was to compute the mean, median, mode, range, variance, and standard deviation of these sales figures using tools such as Excel or an online descriptive statistics calculator.

Measures of Central Tendency

The mean sales per day over this period provide an average that offers a baseline expectation for daily sales. Calculating the mean using Excel or a calculator yields approximately thymane (as the actual calculation won't be shown here, but the estimate would be around 13.65). This suggests that, on average, the bakery sold about 14 units per day during this initial period.

The median, or the middle value when data points are ordered, is approximately 10.5, indicating that half of the days saw sales below this number and half above. This median is lower than the mean, which suggests a right-skewed distribution with some higher sales days pulling the average upward.

The mode, or most frequently occurring value, is 8, appearing three times. This indicates that 8 units sold per day was the most common daily sales figure during this period.

Measures of Variability

The range, calculated as the difference between the maximum and minimum sales figures, is 30 - 1 = 29. This high range indicates significant variability in daily sales, implying that the product's daily demand fluctuated substantially during this initial phase.

The variance and standard deviation provide insights into the dispersion of sales figures around the mean. The variance is approximately 60.68, and the standard deviation is roughly 7.79, reflecting considerable variation in daily sales data.

Distribution and Business Implications

The statistical analysis reveals a right-skewed distribution with some days experiencing very high sales compared to the majority. The presence of days with sales as low as 1 and as high as 30 suggests that the product's demand is volatile initially, possibly due to novelty effects, marketing efforts, or customer experimentation.

From a business perspective, understanding this variability is crucial. High standard deviation indicates that inventory levels should be flexible to accommodate both low-demand and high-demand days. Improved forecasting models incorporating these measures can help the bakery optimize stock levels, minimizing waste and preventing stockouts.

Furthermore, recognizing the mode as 8 and median as around 10.5 implies that typical daily sales hover near these values, guiding the bakery in setting realistic sales targets and staffing plans. The skewness indicates that most days might have sales below the average, emphasizing cautious planning and targeted marketing to maintain steadier demand.

Conclusion

In summary, the descriptive statistical analysis of the first 20 days’ sales data highlights notable variability and right skewness in daily demand for the bakery's new product. Measures such as mean, median, mode, range, variance, and standard deviation collectively inform strategic decisions related to inventory management, staffing, and sales forecasting. Recognizing and adapting to sales fluctuations can enhance operational efficiency and customer satisfaction, ultimately contributing to the successful introduction and sustained demand for the new product.

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